The Scientist–AI Research System: An Integrated Working Standard for War-Related Environmental Contamination

Abstract

This paper integrates six methodological contributions into a working standard for research on war-related environmental contamination. It specifies how the Laboratory of Military Ecotones and Laboratory of Information Systems will organize their cognitive and empirical work.

The standard begins with the environmental problem rather than a discipline, dataset, institution, or method. War-related contamination is treated as a process connecting military events, damaged infrastructure, post-war management, environmental transformation, transport, exposure, human activity, and delayed consequences.

The operative cognitive unit is the scientist–AI system. The expert defines the object, formulates problems, evaluates evidence, selects verification procedures, rejects unacceptable results, and assumes responsibility. AI supports searching, translation, classification, comparison, connection, and reformulation; its system, version, and contribution remain documented.

The research cycle includes problem formulation, evidence classification, competing hypotheses, discriminating observations, field verification, interpretation, model revision, and formulation of problems. Six information statuses—Observed, Documented, Reconstructed, Inferred, Predicted, and Verified—remain distinguishable.

The Laboratory of Military Ecotones investigates war-transformed environmental systems. The Laboratory of Information Systems preserves provenance, uncertainty, analytical relationships, hypothesis histories, and AI-assisted cognitive records. The standard’s adequacy depends on procedural transparency, empirical verification, and demonstrated progress toward recognizing and resolving environmental problems.